Python networkx.read_gml方法代碼示例

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def read_graph(self, subgraph_file=None):
        if subgraph_file is None:
            subraph_file = self.context_graph_file
        logging.info("Writing graph.")
        # write the graph out
        file_format = subgraph_file.split(".")[-1]
        if file_format == "graphml":
            return nx.read_graphml(subgraph_file)
        elif file_format == "gml":
            return nx.read_gml(subgraph_file)
        elif file_format == "gexf":
            return nx.read_gexf(subgraph_file)
        elif file_format == "net":
            return nx.read_pajek(subgraph_file)
        elif file_format == "yaml":
            return nx.read_yaml(subgraph_file)
        elif file_format == "gpickle":
            return nx.read_gpickle(subgraph_file)
        else:
            logging.warning("File format not found, returning empty graph.")
        return nx.MultiDiGraph() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def test_relabel_duplicate(self):
        data = """
graph
[
	label	""
	directed	1
	node
	[
		id	0
		label	"same"
	]
	node
	[
		id	1
		label	"same"
	]
]
"""
        fh = io.BytesIO(data.encode('UTF-8'))
        fh.seek(0)
        assert_raises(
            nx.NetworkXError, nx.read_gml, fh, label='label') 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def test_relabel_duplicate(self):
        data = """
graph
[
        label   ""
        directed        1
        node
        [
                id      0
                label   "same"
        ]
        node
        [
                id      1
                label   "same"
        ]
]
"""
        fh = io.BytesIO(data.encode('UTF-8'))
        fh.seek(0)
        assert_raises(
            nx.NetworkXError, nx.read_gml, fh, label='label') 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def main():
    args = get_options()

    # make sure trailing forward slash is present
    args.output_dir = os.path.join(args.output_dir, "")

    # Create temporary directory
    temp_dir = os.path.join(tempfile.mkdtemp(dir=args.output_dir), "")

    # Load isolate names
    seen = set()
    isolate_names = []
    with open(args.output_dir + "gene_data.csv", 'r') as infile:
        next(infile)
        for line in infile:
            iso = line.split(",")[0]
            if iso not in seen:
                isolate_names.append(iso)
                seen.add(iso)

    # Load graph
    G = nx.read_gml(args.output_dir + "final_graph.gml")

    #Write out core/pan-genome alignments
    if args.aln == "pan":
        if args.verbose: print("generating pan genome MSAs...")
        generate_pan_genome_alignment(G, temp_dir, args.output_dir, args.n_cpu,
                                      args.alr, isolate_names)
        core_nodes = get_core_gene_nodes(G, args.core, len(args.input_files))
        concatenate_core_genome_alignments(core_nodes, args.output_dir)
    elif args.aln == "core":
        if args.verbose: print("generating core genome MSAs...")
        generate_core_genome_alignment(G, temp_dir, args.output_dir,
                                       args.n_cpu, args.alr, isolate_names,
                                       args.core, len(isolate_names))

    # remove temporary directory
    shutil.rmtree(temp_dir)

    return 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def ReadGraph(graphName):
    if (graphName.find("gml") >= 0):
        g= nx.read_gml(graphName)
    elif (graphName.find("gexf") >= 0):
        g= nx.read_gexf(graphName)
    elif (graphName.find("graphml") >= 0):
        g=nx.read_graphml(graphName)
    else:
        print "ERROR, could not determine graph format " + graphName
        sys.exit(0)
    return g 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def test_read_gml(self):
        (fd, fname) = tempfile.mkstemp()
        fh = open(fname, 'w')
        fh.write(self.simple_data)
        fh.close()
        Gin = nx.read_gml(fname, label='label')
        G = nx.parse_gml(self.simple_data, label='label')
        assert_equals(sorted(G.nodes(data=True)), sorted(Gin.nodes(data=True)))
        assert_equals(sorted(G.edges(data=True)), sorted(Gin.edges(data=True)))
        os.close(fd)
        os.unlink(fname) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def load_graphs(graph_files, n_cpu=1):
    for graph_file in graph_files:
        if not os.path.isfile(graph_file):
            print("Missing:", graph_file)
            raise RuntimeError("Missing graph file!")

    graphs = [nx.read_gml(graph_file) for graph_file in tqdm(graph_files)]
    isolate_names = list(
        itertools.chain.from_iterable(
            [G.graph['isolateNames'] for G in graphs]))

    member_count = 0
    node_count = 0
    id_mapping = []
    for i, G in enumerate(graphs):
        id_mapping.append({})
        # relabel nodes to be consecutive integers from 1
        mapping = {}
        for n in G.nodes():
            mapping[n] = node_count
            node_count += 1
        G = nx.relabel_nodes(G, mapping, copy=True)

        # set up edge members and remove conflicts.
        for e in G.edges():
            G[e[0]][e[1]]['members'] = intbitset([
                m + member_count for m in conv_list(G[e[0]][e[1]]['members'])
            ])

        # set up node parameters and remove conflicts.
        max_mem = -1
        for n in G.nodes():
            ncentroids = []
            for sid in G.nodes[n]['centroid'].split(";"):
                nid = update_sid(sid, member_count)
                id_mapping[i][sid] = nid
                if "refound" not in nid:
                    ncentroids.append(nid)
            G.nodes[n]['centroid'] = ncentroids
            new_ids = set()
            for sid in conv_list(G.nodes[n]['seqIDs']):
                nid = update_sid(sid, member_count)
                id_mapping[i][sid] = nid
                new_ids.add(nid)
            G.nodes[n]['seqIDs'] = new_ids
            G.nodes[n]['protein'] = del_dups(G.nodes[n]['protein'].replace(
                '*', 'J').split(";"))
            G.nodes[n]['dna'] = del_dups(G.nodes[n]['dna'].split(";"))
            G.nodes[n]['lengths'] = conv_list(G.nodes[n]['lengths'])
            G.nodes[n]['longCentroidID'][1] = update_sid(
                G.nodes[n]['longCentroidID'][1], member_count)
            G.nodes[n]['members'] = intbitset(
                [m + member_count for m in conv_list(G.nodes[n]['members'])])
            max_mem = max(max_mem, max(G.nodes[n]['members']))

        member_count = max_mem + 1
        graphs[i] = G

    return graphs, isolate_names, id_mapping 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def read_gml(path, label='label', destringizer=None):
    """Read graph in GML format from path.

    Parameters
    ----------
    path : filename or filehandle
        The filename or filehandle to read from.

    label : string, optional
        If not None, the parsed nodes will be renamed according to node
        attributes indicated by ``label``. Default value: ``'label'``.

    destringizer : callable, optional
        A destringizer that recovers values stored as strings in GML. If it
        cannot convert a string to a value, a ``ValueError`` is raised. Default
        value : ``None``.

    Returns
    -------
    G : NetworkX graph
        The parsed graph.

    Raises
    ------
    NetworkXError
        If the input cannot be parsed.

    See Also
    --------
    write_gml, parse_gml

    Notes
    -----
    The GML specification says that files should be ASCII encoded, with any
    extended ASCII characters (iso8859-1) appearing as HTML character entities.

    References
    ----------
    GML specification:
    http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html

    Examples
    --------
    >>> G = nx.path_graph(4)
    >>> nx.write_gml(G, 'test.gml')
    >>> H = nx.read_gml('test.gml')
    """
    def filter_lines(lines):
        for line in lines:
            try:
                line = line.decode('ascii')
            except UnicodeDecodeError:
                raise NetworkXError('input is not ASCII-encoded')
            if not isinstance(line, str):
                lines = str(lines)
            if line and line[-1] == '\n':
                line = line[:-1]
            yield line

    G = parse_gml_lines(filter_lines(path), label, destringizer)
    return G 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def write_gml(G, path, stringizer=None):
    """Write a graph ``G`` in GML format to the file or file handle ``path``.

    Parameters
    ----------
    G : NetworkX graph
        The graph to be converted to GML.

    path : filename or filehandle
        The filename or filehandle to write. Files whose names end with .gz or
        .bz2 will be compressed.

    stringizer : callable, optional
        A stringizer which converts non-int/non-float/non-dict values into
        strings. If it cannot convert a value into a string, it should raise a
        ``ValueError`` to indicate that. Default value: ``None``.

    Raises
    ------
    NetworkXError
        If ``stringizer`` cannot convert a value into a string, or the value to
        convert is not a string while ``stringizer`` is ``None``.

    See Also
    --------
    read_gml, generate_gml

    Notes
    -----
    Graph attributes named ``'directed'``, ``'multigraph'``, ``'node'`` or
    ``'edge'``,node attributes named ``'id'`` or ``'label'``, edge attributes
    named ``'source'`` or ``'target'`` (or ``'key'`` if ``G`` is a multigraph)
    are ignored because these attribute names are used to encode the graph
    structure.

    Examples
    --------
    >>> G = nx.path_graph(4)
    >>> nx.write_gml(G, "test.gml")

    Filenames ending in .gz or .bz2 will be compressed.

    >>> nx.write_gml(G, "test.gml.gz")
    """
    for line in generate_gml(G, stringizer):
        path.write((line + '\n').encode('ascii'))


# fixture for nose 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_gml [as 別名]
def write_gml(G, path, stringizer=None):
    """Write a graph `G` in GML format to the file or file handle `path`.

    Parameters
    ----------
    G : NetworkX graph
        The graph to be converted to GML.

    path : filename or filehandle
        The filename or filehandle to write. Files whose names end with .gz or
        .bz2 will be compressed.

    stringizer : callable, optional
        A `stringizer` which converts non-int/non-float/non-dict values into
        strings. If it cannot convert a value into a string, it should raise a
        `ValueError` to indicate that. Default value: None.

    Raises
    ------
    NetworkXError
        If `stringizer` cannot convert a value into a string, or the value to
        convert is not a string while `stringizer` is None.

    See Also
    --------
    read_gml, generate_gml, literal_stringizer

    Notes
    -----
    Graph attributes named 'directed', 'multigraph', 'node' or
    'edge', node attributes named 'id' or 'label', edge attributes
    named 'source' or 'target' (or 'key' if `G` is a multigraph)
    are ignored because these attribute names are used to encode the graph
    structure.

    GML files are stored using a 7-bit ASCII encoding with any extended
    ASCII characters (iso8859-1) appearing as HTML character entities.
    Without specifying a `stringizer`/`destringizer`, the code is capable of
    handling `int`/`float`/`str`/`dict`/`list` data as required by the GML
    specification.  For other data types, you need to explicitly supply a
    `stringizer`/`destringizer`.

    For additional documentation on the GML file format, please see the
    `GML website <http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html>`_.

    See the module docstring :mod:`networkx.readwrite.gml` for additional details.

    Examples
    --------
    >>> G = nx.path_graph(4)
    >>> nx.write_gml(G, "test.gml")

    Filenames ending in .gz or .bz2 will be compressed.

    >>> nx.write_gml(G, "test.gml.gz")
    """
    for line in generate_gml(G, stringizer):
        path.write((line + '\n').encode('ascii'))


# fixture for nose